1. You are working with a group of genetics researchers analyzing data generated by gene sequencers. The data is stored in Cloud Storage. The analysis requires running a series of six programs, each of which will output data that is used by the next process in the pipeline. The final result set is loaded into BigQuery. What tool would you recommend for orchestrating this workflow?

2. A group of IoT sensors is sending streaming data to a Cloud Pub/Sub topic. A Cloud Dataflow service pulls messages from the topic and reorders the messages sorted by event time. A message is expected from each sensor every minute. If a message is not received from a sensor, the stream processing application should use the average of the values in the last four messages. What kind of window would you use to implement the missing data logic?

3. Your department is migrating some stream processing to GCP and keeping some on premises. You are tasked with designing a way to share data from on-premises pipelines that use Kafka with GPC data pipelines that use Cloud Pub/Sub. How would you do that?

4. You are designing a data pipeline to populate a sales data mart. The sponsor of the project has had quality control problems in the past and has defined a set of rules for filtering out bad data before it gets into the data mart. At what stage of the data pipeline would you implement those rules?

5. An on-premises data warehouse is currently deployed using HBase on Hadoop. You want to migrate the database to GCP. You could continue to run HBase within a Cloud Dataproc cluster, but what other option would help ensure consistent performance and support the HBase API?

6. A large enterprise using GCP has recently acquired a startup that has an IoT platform. The acquiring company wants to migrate the IoT platform from an on-premises data center to GCP and wants to use Google Cloud managed services whenever possible. What GCP service would you recommend for ingesting IoT data?

7. You are using Cloud Pub/Sub to buffer records from an application that generates a stream of data based on user interactions with a website. The messages are read by another service that transforms the data and sends it to a machine learning model that will use it for training. A developer has just released some new code, and you notice that messages are sent repeatedly at 10-minute intervals. What might be the cause of this problem?

8. It is considered a good practice to make your processing logic idempotent when consuming messages from a Cloud Pub/Sub topic. Why is that?

9. A team of data warehouse developers is migrating a set of legacy Python scripts that have been used to transform data as part of an ETL process. They would like to use a service that allows them to use Python and requires minimal administration and operations support. Which GCP service would you recommend?

10. The business owners of a data warehouse have determined that the current design of the data warehouse is not meeting their needs. In addition to having data about the state of systems at certain points in time, they need to know about all the times that data changed between those points in time. What kind of data warehousing pipeline should be used to meet this new requirement?

11. A team of developers wants to create standardized patterns for processing IoT data. Several teams will use these patterns. The developers would like to support collaboration and facilitate the use of patterns for building streaming data pipelines. What component should they use?

12. You need to run several map reduce jobs on Hadoop along with one Pig job and four PySpark jobs. When you ran the jobs on premises, you used the department’s Hadoop cluster. Now you are running the jobs in GCP. What configuration for running these jobs would you recommend?